
Pearson Correlation Coefficient [1]} is a statistics that measures linear correlation between two variables. It has a value between \(-1\)  and \(+1\) , where a value of 0 means no linear correlation, and values greater than 0 indicates positive correlations and vise versa. It is reported for the sentence-level QE task.

MAE and RMSE, i.e., mean absolute error and root mean squared error, are two of the most common metrics used to measure accuracy of continuous variables. They are also reported for the sentence-level QE task.

Matthews Correlation Coefficient (MCC) [2]} is used to measure the quality of binary classifications. Its value also ranges from \(-1\)  to \(+1\) , where \(-1\)  and \(+1\)  mean total disagreement and total agreement, and 0 is close to random guesses. The MCC metric is reported in the word-level QE task.

F1-BAD and F1-OK are the two F1 scores for tokens labeled with “BAD” and “OK”, where the F1 score is a measure of accuracy calculated from the precision and recall values.

